Competition and restaurant online review manipulations: A dynamic panel data analysis

被引:1
|
作者
Li, Hengyun [1 ]
Ji, Haipeng [1 ]
Luo, Jian Ming [2 ]
Zhang, Ziqiong [3 ]
机构
[1] Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Hong Kong, Peoples R China
[2] Macau Univ Sci & Technol, Sch Liberal Arts, Macau, Peoples R China
[3] Harbin Inst Technol, Sch Management, 92 West Dazhi St, Harbin 150001, Peoples R China
关键词
Review manipulation; Self; -promotion; Demotion; Competition; Restaurant; FAKE REVIEWS; CONSUMER REVIEWS; IMPACT; BEHAVIOR; QUALITY; PRODUCT;
D O I
10.1016/j.ijhm.2023.103605
中图分类号
F [经济];
学科分类号
02 ;
摘要
It is important to understand business online review manipulations, through which consumers can make better choice and platforms' reputations can be maintained. Based on monthly panel data of 970 restaurants across 14 years in a metropolitan city in the US, this study investigates the impact of competition on both restaurant positive and negative online review manipulations. This study constructed a new competition index reflecting competitors' quantity, quality, and negative influence of distance on the intensity of competition using the Gaussian kernel function, and the empirical results show: (1) both positive and negative review manipulations are positively influenced by competition; (2) the influence of the same cuisine competitors on the focal restaurant's review manipulations are stronger than their counterpart competitors; and (3) the competition's in-fluence on positive review manipulation is stronger for high-priced than low-priced restaurants, but no difference exists regarding restaurant review demotion received. This study enriches the online review manipulation literature.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Economic Growth And Carbon Emission: A Dynamic Panel Data Analysis
    Bakirtas, Ibrahim
    Bayrak, Seyhat
    Cetin, Atalay
    EUROPEAN JOURNAL OF SUSTAINABLE DEVELOPMENT, 2014, 3 (04): : 91 - 102
  • [32] Bayesian analysis of quantile regression for censored dynamic panel data
    Kobayashi, Genya
    Kozumi, Hideo
    COMPUTATIONAL STATISTICS, 2012, 27 (02) : 359 - 380
  • [33] Riskiness of lending to small businesses: a dynamic panel data analysis />
    Moyi, Eliud
    JOURNAL OF RISK FINANCE, 2019, 20 (01) : 94 - 110
  • [34] Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data
    Zhang, Hao
    Kim, Gunhee
    Xing, Eric P.
    KDD'15: PROCEEDINGS OF THE 21ST ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2015, : 1425 - 1434
  • [35] A dynamic online tool for cardiovascular and ECG data analysis
    Markert, Michael
    Alizadeh, Elham Ataei
    Zellner, Dietmar
    Trautmann, Thomas
    JOURNAL OF PHARMACOLOGICAL AND TOXICOLOGICAL METHODS, 2022, 117
  • [36] A Market Analytics Approach to Restaurant Review Data
    Tsubiks, Olga
    Keselj, Vlado
    PROCEEDINGS OF THE ACM SYMPOSIUM ON DOCUMENT ENGINEERING (DOCENG 2018), 2018,
  • [37] Examining the Role of Semantic Similarity in Online Restaurant Review Evaluations
    Li, Lin
    Ren, Gang
    Hong, Taeho
    Yang, Sung-Byung
    AMCIS 2020 PROCEEDINGS, 2020,
  • [38] Did residential electricity rates fall after retail competition? A dynamic panel analysis
    Swadley, Adam
    Yuecel, Mine
    ENERGY POLICY, 2011, 39 (12) : 7702 - 7711
  • [39] Interconnectedness between online review valence, brand, and restaurant performance
    Wang, Yiqi
    Kim, Jewoo
    JOURNAL OF HOSPITALITY AND TOURISM MANAGEMENT, 2021, 48 : 138 - 145
  • [40] ANALYSIS OF AN ONLINE TAEKWONDO COMPETITION
    Asenov, Asen
    PEDAGOGIKA-PEDAGOGY, 2020, 92 (07): : 97 - 105